Underwater image super-resolution using multi-stage information distillation networks

Recently, single image super-resolution (SISR) has been widely applied in the fields of underwater robot vision and obtained remarkable performance. However, most current methods generally suffered from the problem of a heavy burden on computational resources with large model sizes, which limited their real-world underwater robotic applications. In this paper, we introduce and tackle the super resolution (SR) problem for underwater robot vision and provide an efficient solution for near real-time applications. We present a novel lightweight multi-stage information distillation network, named MSIDN, for better balancing performance against applicability, which aggregates the local distilled features from different stages for more powerful feature representation. Moreover, a novel recursive residual feature distillation (RRFD) module is constructed to progressively extract useful features with a modest number of parameters in each stage. We also propose a channel interaction & distillation (CI&D) module that employs channel split operation on the preceding features to produce two-part features and utilizes the inter channel-wise interaction information between them to generate the distilled features, which can effectively extract the useful information of current stage without extra parameters. Besides, we present USR-2K dataset, a collection of over 1.6K samples for large-scale underwater image SR training, and a testset with an additional 400 samples for benchmark evaluation. Extensive experiments on several standard benchmark datasets show that the proposed MSIDN can provide state-of-the-art or even better performance in both quantitative and qualitative measurements.     

跨行政区游憩空间柔性一体化研究 ——以高莱茵河沿岸地区为例

随着城市化与区域一体化的迅速发展,不同行政区之间的联动关系越来越紧密,这种联动关系在城市各功能空间的设计上有所体现,更渗透到了与市民息息相关的游憩空间建构之中。受制于行政管理等方面的原因,在跨行政区的游憩空间一体化实施过程中,往往会采取一系列柔性措施。以欧洲高莱茵河沿岸地区为研究对象,分析高莱茵河沿岸地区游憩空间的发展与现状,总结其游憩空间体系的构建特点,为中国跨城市河流沿岸的游憩空间柔性一体化建构提供策略与建议。     

基于VMD和BSA-KELM的高陡边坡位移预测模型研究

边坡位移的时间序列曲线存在复杂的非线性特性,传统的预测模型精度不足以满足预测要求。为此提出了基于变分模态分解的鸟群优化-核极限学习机的预测模型,并用于河北省某水泥厂的边坡位移预测。该方法首先采用VMD把边坡位移序列分解为一系列的有限带宽的子序列,再对各子序列分别采用相空间重构并用核极限学习机预测,采用鸟群算法优化相空间重构的嵌入维度和KELM中惩罚系数和核参数三个数值,以取得最优预测模型。最后将各个子序列预测值叠加,得到边坡位移的最终预测值。结果表明：和KELM、BSA-KELM、EEMD-BSA-KELM模型相比,基于VMD的BSA-KELM预测精度更高,为边坡位移的预测提供一种有效的方法。     

Efficient Flexible M-Tree Bulk Loading Using FastMap and Space-Filling Curves

Many database applications currently deal with objects in a metric space. Examples of such objects include unstructured multimedia objects and points of interest (POIs) in a road network. The M-tree is a dynamic index structure that facilitates an efficient search for objects in a metric space. Studies have been conducted on the bulk loading of large datasets in an M-tree. However, because previous algorithms involve excessive distance computations and disk accesses, they perform poorly in terms of their index construction and search capability. This study proposes two efficient M-tree bulk loading algorithms. Our algorithms minimize the number of distance computations and disk accesses using FastMap and a space-filling curve, thereby significantly improving the index construction and search performance. Our second algorithm is an extension of the first, and it incorporates a partitioning clustering technique and flexible node architecture to further improve the search performance. Through the use of various synthetic and real-world datasets, the experimental results demonstrated that our algorithms improved the index construction performance by up to three orders of magnitude and the search performance by up to 20.3 times over the previous algorithm.     

Reduced‐order method for mathematical modeling of multiphase dc‐dc converter

A multiphase dc‐dc converter is effective for miniaturization and achieving high‐power density in a switching power supply. However, its mathematical modeling becomes complex as the phase number of the circuit increases. This study proposes a new modeling method to derive a reduced‐order method in a simple manner. The frequency characteristics of the reduced‐order model are fit to those of the original mathematical model of the multiphase dc‐dc converter. Therefore, the efficacy of the proposed method is validated.     

Human responses to high levels of carbon dioxide and air temperature

In this study, 30 subjects were exposed to different combinations of air temperature (T_a: 24, 27, and 30°C) and CO₂ level (8000, 10 000, and 12 000 ppm) in a high-humidity (RH: 85%) underground climate chamber. Subjective assessments, physiological responses, and cognitive performance were investigated. The results showed that as compared with exposure to T_a = 24°C, exposure to 30°C at all CO₂ levels caused subjects to feel uncomfortably warm and experience stronger odor intensity, while increased mental effort and greater intensity of acute health symptoms were reported. However, no significant effects of T_a on task performance or physiological responses were found. This indicated that subjects had to exert more effort to maintain their performance in an uncomfortably warm environment. Increasing CO₂ from 8000 to 12 000 ppm at all T_a caused subjects to report higher rates of headache, fatigue, agitation, and feeling depressed, although the results were statistically significant only at 24 and 27°C. The text typing performance and systolic blood pressure (SBP) decreased significantly at this exposure, whereas diastolic blood pressure (DBP) and thermal discomfort increased significantly. These effects suggest higher arousal/stress. No significant interaction effect of T_a and CO₂ concentration on human responses was identified.     

Chemical Bonding by the Chemical Orthogonal Space of Reactivity

The fashionable Parr–Pearson (PP) atoms-in-molecule/bonding (AIM/AIB) approach for determining the exchanged charge necessary for acquiring an equalized electronegativity within a chemical bond is refined and generalized here by introducing the concepts of chemical power within the chemical orthogonal space (COS) in terms of electronegativity and chemical hardness. Electronegativity and chemical hardness are conceptually orthogonal, since there are opposite tendencies in bonding, i.e., reactivity vs. stability or the HOMO-LUMO middy level vs. the HOMO-LUMO interval (gap). Thus, atoms-in-molecule/bond electronegativity and chemical hardness are provided for in orthogonal space (COS), along with a generalized analytical expression of the exchanged electrons in bonding. Moreover, the present formalism surpasses the earlier Parr–Pearson limitation to the context of hetero-bonding molecules so as to also include the important case of covalent homo-bonding. The connections of the present COS analysis with PP formalism is analytically revealed, while a numerical illustration regarding the patterning and fragmentation of chemical benchmarking bondings is also presented and fundamental open questions are critically discussed.     

Bioinspired Triboelectric Soft Robot Driven by Mechanical Energy

A sustainable power source is a key technical challenge for practical applications of electrically responsive soft robots, especially the required voltage is over several thousand volts. Here, a practicable new technology, triboelectric soft robot (TESR) system with the primary characteristics of power source from mechanical energy, is developed. At its heart is TESR with bioinspired architectures made of soft-deformable body and two triboelectric adhesion feet, which is driven and accurately controlled through triboelectric effect, while reaching maximum crawling speeds of 14.9 mm s⁻¹ on the acrylic surface. The characteristics of the TESR, including displacement and force, are tested and simulated under the power of a rotary freestanding triboelectric nanogenerator (RF-TENG). Crawling of TESR is successfully realized on different materials surfaces and different angle slopes under the driven of RF-TENG. Furthermore, a real-time visual monitoring platform, in which TESR carries a micro camera to transmit images in a long narrow tunnel, is also achieved successfully, indicating that it can be used for fast diagnosis in an area inaccessible to human beings in the future. This study offers a new insight into the sustainable power source technologies suitable for electrically responsive soft robots and contributes to expanding the applicability of TENGs.     

变分自编码器模型综述

变分自编码器（VAE）作为深度隐空间生成模型的一种，近年来其表现性能取得了极大的成功，尤其是在图像生成方面。变分自编码器模型作为无监督式特征学习的重要工具之一，可以通过学习隐编码空间与数据生成空间的特征映射，进而在输出端重构生成输入数据。梳理了传统变分自编码器模型及其衍生变体模型的发展与研究现状，并就此做了总结和对比，最后分析了变分自编码器模型存在的问题与挑战，并就可能的发展趋势做了展望。     

Photomontage in the Present Perfect Continuous

In its first instance as art practice among the historical avant-garde, photomontage was considered indispensable for its claim to intervene in perceptual processes, stimulating a critical mode of apprehension that would redirect the viewer away from conventions of aesthetic experience and towards a lived reception of art with pronounced relevance to the sociopolitical landscape. The effect was understood as structural, that is, activated not so much by direct political content, but by the stark and shocking effects of juxtaposition. By this measure, one challenge to contemporary photomontage is clear: in a postindustrial and postdigital visual landscape dominated by the structural fragmentation of the attention economy, the ‘simultaneity of the radically disparate’ (as Peter Bürger put it) might no longer present as heterodoxy but rather threaten to sink into invisibility. Yet with the migration off-screen of the effects of electronic media, a new urgency around moving photomontage structures into physical, public space is rising in contemporary practices. Shannon Ebner’s multi-part project A Hudson Yard (2014–15) is emblematic of the new ways in which artists are manipulating photomontage as a form of fully sensory experience that gives the medium room to play critically in both virtual and material space. By constructing subtle interruptions of naturalised commercial space, A Hudson Yard activates a détournement of instrumentalised language, using structures of juxtaposition to divert the discursive surfaces of public space away from consumption and towards what could be called a public poesis.